-------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\My Documents\PSRMLaptop\Hobby\Nuclear Latency\FPA_replication\Analysis_Main_log.log
  log type:  text
 opened on:   1 Nov 2024, 16:29:40

. 
. *Table 3
. 
. use "nuclear_latency_panel.dta", clear
(Written by R.              )

. 
. sort ccode year

. xi i.year
i.year            _Iyear_1950-2010    (naturally coded; _Iyear_1950 omitted)

. 
. xtset ccode year

Panel variable: ccode (unbalanced)
 Time variable: year, 1950 to 2010, but with a gap
         Delta: 1 unit

. 
. gen Nu_std_lagged = l.Nu_std
(200 missing values generated)

. 
. gen support_US_lagged = l.support_US_std
(199 missing values generated)

. gen support_USSR_lagged = l.support_USSR_std
(199 missing values generated)

. gen support_UK_lagged = l.support_UK_std
(199 missing values generated)

. gen support_France_lagged = l.support_France_std
(199 missing values generated)

. gen support_China_lagged = l.support_China_std
(199 missing values generated)

. 
. 
. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,487
Group variable: ccode                           Number of groups  =        198

R-squared:                                      Obs per group:
     Within  = 0.9648                                         min =          1
     Between = 0.9996                                         avg =       42.9
     Overall = 0.9923                                         max =         60

                                                F(5,197)          =   33956.92
corr(u_i, Xb) = 0.8195                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 198 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .9093366   .0100448    90.53   0.000     .8895275    .9291456
                                  support_US_lagged |  -.0064031   .0130271    -0.49   0.624    -.0320937    .0192874
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .1037069   .0423932     2.45   0.015     .0201042    .1873096
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .0582491   .0090927     6.41   0.000     .0403176    .0761806
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |  -.1242314   .0328074    -3.79   0.000    -.1889301   -.0595327
                                                    |
                                              _cons |   .0311773   .0024242    12.86   0.000     .0263965     .035958
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .01253948
                                            sigma_e |  .02156329
                                                rho |  .25270808   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. estimates store m1

. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged l2.support_USSR_std l2.support_Ch
> ina_std l2.support_UK_std l2.support_France_std l2.cinc l2.country_dem l2.ln_GNP l2.i.mid l2.IdealPointDistance_US, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      7,378
Group variable: ccode                           Number of groups  =        191

R-squared:                                      Obs per group:
     Within  = 0.9620                                         min =          3
     Between = 0.9993                                         avg =       38.6
     Overall = 0.9925                                         max =         58

                                                F(14,190)         =   11037.64
corr(u_i, Xb) = 0.8059                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 191 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .8749778   .0119198    73.41   0.000     .8514657      .89849
                                  support_US_lagged |  -.0052041   .0153578    -0.34   0.735    -.0354979    .0250896
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .1218442   .0521107     2.34   0.020     .0190544    .2246341
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .0675694   .0107189     6.30   0.000      .046426    .0887128
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |   -.156021    .041153    -3.79   0.000    -.2371964   -.0748455
                                                    |
                                   support_USSR_std |
                                                L2. |  -.0015408   .0034837    -0.44   0.659    -.0084125     .005331
                                                    |
                                  support_China_std |
                                                L2. |   .0012061   .0020534     0.59   0.558    -.0028443    .0052566
                                                    |
                                     support_UK_std |
                                                L2. |  -.0073282    .002746    -2.67   0.008    -.0127447   -.0019118
                                                    |
                                 support_France_std |
                                                L2. |   .0025757   .0015849     1.63   0.106    -.0005506    .0057019
                                                    |
                                               cinc |
                                                L2. |    .525786   .2073758     2.54   0.012     .1167314    .9348405
                                                    |
                                        country_dem |
                                                L2. |  -.0010102   .0006983    -1.45   0.150    -.0023876    .0003671
                                                    |
                                             ln_GNP |
                                                L2. |   .0023968   .0005693     4.21   0.000     .0012738    .0035198
                                                    |
                                             L2.mid |
                                                 1  |  -.0002986    .000642    -0.47   0.642     -.001565    .0009677
                                                    |
                              IdealPointDistance_US |
                                                L2. |   .0008585   .0005742     1.50   0.137    -.0002742    .0019912
                                                    |
                                              _cons |  -.0114136   .0105198    -1.08   0.279    -.0321641    .0093369
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .01465786
                                            sigma_e |   .0207191
                                                rho |  .33355294   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. estimates store m2

. 
. esttab m1 m2 using Table3.tex, se star(+ 0.10 * 0.05 ** 0.01) replace
(output written to Table3.tex)

. 
. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged l2.support_USSR_std l2.support_Ch
> ina_std l2.support_UK_std l2.support_France_std l2.cinc l2.country_dem l2.ln_GNP l2.i.mid l2.IdealPointDistance_US, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      7,378
Group variable: ccode                           Number of groups  =        191

R-squared:                                      Obs per group:
     Within  = 0.9620                                         min =          3
     Between = 0.9993                                         avg =       38.6
     Overall = 0.9925                                         max =         58

                                                F(14,190)         =   11037.64
corr(u_i, Xb) = 0.8059                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 191 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .8749778   .0119198    73.41   0.000     .8514657      .89849
                                  support_US_lagged |  -.0052041   .0153578    -0.34   0.735    -.0354979    .0250896
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .1218442   .0521107     2.34   0.020     .0190544    .2246341
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .0675694   .0107189     6.30   0.000      .046426    .0887128
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |   -.156021    .041153    -3.79   0.000    -.2371964   -.0748455
                                                    |
                                   support_USSR_std |
                                                L2. |  -.0015408   .0034837    -0.44   0.659    -.0084125     .005331
                                                    |
                                  support_China_std |
                                                L2. |   .0012061   .0020534     0.59   0.558    -.0028443    .0052566
                                                    |
                                     support_UK_std |
                                                L2. |  -.0073282    .002746    -2.67   0.008    -.0127447   -.0019118
                                                    |
                                 support_France_std |
                                                L2. |   .0025757   .0015849     1.63   0.106    -.0005506    .0057019
                                                    |
                                               cinc |
                                                L2. |    .525786   .2073758     2.54   0.012     .1167314    .9348405
                                                    |
                                        country_dem |
                                                L2. |  -.0010102   .0006983    -1.45   0.150    -.0023876    .0003671
                                                    |
                                             ln_GNP |
                                                L2. |   .0023968   .0005693     4.21   0.000     .0012738    .0035198
                                                    |
                                             L2.mid |
                                                 1  |  -.0002986    .000642    -0.47   0.642     -.001565    .0009677
                                                    |
                              IdealPointDistance_US |
                                                L2. |   .0008585   .0005742     1.50   0.137    -.0002742    .0019912
                                                    |
                                              _cons |  -.0114136   .0105198    -1.08   0.279    -.0321641    .0093369
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .01465786
                                            sigma_e |   .0207191
                                                rho |  .33355294   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. margins, dydx(support_US_lagged) at(Nu_std_lagged = (0(0.01)1)) force

Average marginal effects                                 Number of obs = 7,378
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  support_US_lagged
1._at:   Nu_std_lagged =   0
2._at:   Nu_std_lagged = .01
3._at:   Nu_std_lagged = .02
4._at:   Nu_std_lagged = .03
5._at:   Nu_std_lagged = .04
6._at:   Nu_std_lagged = .05
7._at:   Nu_std_lagged = .06
8._at:   Nu_std_lagged = .07
9._at:   Nu_std_lagged = .08
10._at:  Nu_std_lagged = .09
11._at:  Nu_std_lagged =  .1
12._at:  Nu_std_lagged = .11
13._at:  Nu_std_lagged = .12
14._at:  Nu_std_lagged = .13
15._at:  Nu_std_lagged = .14
16._at:  Nu_std_lagged = .15
17._at:  Nu_std_lagged = .16
18._at:  Nu_std_lagged = .17
19._at:  Nu_std_lagged = .18
20._at:  Nu_std_lagged = .19
21._at:  Nu_std_lagged =  .2
22._at:  Nu_std_lagged = .21
23._at:  Nu_std_lagged = .22
24._at:  Nu_std_lagged = .23
25._at:  Nu_std_lagged = .24
26._at:  Nu_std_lagged = .25
27._at:  Nu_std_lagged = .26
28._at:  Nu_std_lagged = .27
29._at:  Nu_std_lagged = .28
30._at:  Nu_std_lagged = .29
31._at:  Nu_std_lagged =  .3
32._at:  Nu_std_lagged = .31
33._at:  Nu_std_lagged = .32
34._at:  Nu_std_lagged = .33
35._at:  Nu_std_lagged = .34
36._at:  Nu_std_lagged = .35
37._at:  Nu_std_lagged = .36
38._at:  Nu_std_lagged = .37
39._at:  Nu_std_lagged = .38
40._at:  Nu_std_lagged = .39
41._at:  Nu_std_lagged =  .4
42._at:  Nu_std_lagged = .41
43._at:  Nu_std_lagged = .42
44._at:  Nu_std_lagged = .43
45._at:  Nu_std_lagged = .44
46._at:  Nu_std_lagged = .45
47._at:  Nu_std_lagged = .46
48._at:  Nu_std_lagged = .47
49._at:  Nu_std_lagged = .48
50._at:  Nu_std_lagged = .49
51._at:  Nu_std_lagged =  .5
52._at:  Nu_std_lagged = .51
53._at:  Nu_std_lagged = .52
54._at:  Nu_std_lagged = .53
55._at:  Nu_std_lagged = .54
56._at:  Nu_std_lagged = .55
57._at:  Nu_std_lagged = .56
58._at:  Nu_std_lagged = .57
59._at:  Nu_std_lagged = .58
60._at:  Nu_std_lagged = .59
61._at:  Nu_std_lagged =  .6
62._at:  Nu_std_lagged = .61
63._at:  Nu_std_lagged = .62
64._at:  Nu_std_lagged = .63
65._at:  Nu_std_lagged = .64
66._at:  Nu_std_lagged = .65
67._at:  Nu_std_lagged = .66
68._at:  Nu_std_lagged = .67
69._at:  Nu_std_lagged = .68
70._at:  Nu_std_lagged = .69
71._at:  Nu_std_lagged =  .7
72._at:  Nu_std_lagged = .71
73._at:  Nu_std_lagged = .72
74._at:  Nu_std_lagged = .73
75._at:  Nu_std_lagged = .74
76._at:  Nu_std_lagged = .75
77._at:  Nu_std_lagged = .76
78._at:  Nu_std_lagged = .77
79._at:  Nu_std_lagged = .78
80._at:  Nu_std_lagged = .79
81._at:  Nu_std_lagged =  .8
82._at:  Nu_std_lagged = .81
83._at:  Nu_std_lagged = .82
84._at:  Nu_std_lagged = .83
85._at:  Nu_std_lagged = .84
86._at:  Nu_std_lagged = .85
87._at:  Nu_std_lagged = .86
88._at:  Nu_std_lagged = .87
89._at:  Nu_std_lagged = .88
90._at:  Nu_std_lagged = .89
91._at:  Nu_std_lagged =  .9
92._at:  Nu_std_lagged = .91
93._at:  Nu_std_lagged = .92
94._at:  Nu_std_lagged = .93
95._at:  Nu_std_lagged = .94
96._at:  Nu_std_lagged = .95
97._at:  Nu_std_lagged = .96
98._at:  Nu_std_lagged = .97
99._at:  Nu_std_lagged = .98
100._at: Nu_std_lagged = .99
101._at: Nu_std_lagged =   1

-----------------------------------------------------------------------------------
                  |            Delta-method
                  |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
------------------+----------------------------------------------------------------
support_US_lagged |
              _at |
               1  |  -.0052041   .0153578    -0.34   0.735     -.035305    .0248967
               2  |  -.0040013   .0148663    -0.27   0.788    -.0331387    .0251361
               3  |  -.0028297   .0143837    -0.20   0.844    -.0310213    .0253619
               4  |  -.0016892   .0139102    -0.12   0.903    -.0289527    .0255742
               5  |    -.00058   .0134457    -0.04   0.966     -.026933     .025773
               6  |    .000498   .0129903     0.04   0.969    -.0249624    .0259585
               7  |   .0015448    .012544     0.12   0.902     -.023041    .0261307
               8  |   .0025604   .0121071     0.21   0.833     -.021169    .0262899
               9  |   .0035449   .0116794     0.30   0.761    -.0193464    .0264361
              10  |   .0044981   .0112612     0.40   0.690    -.0175734    .0265695
              11  |   .0054201   .0108524     0.50   0.617    -.0158502    .0266903
              12  |   .0063109   .0104532     0.60   0.546     -.014177    .0267987
              13  |   .0071705   .0100636     0.71   0.476    -.0125539    .0268948
              14  |   .0079988   .0096838     0.83   0.409    -.0109811    .0269788
              15  |    .008796   .0093139     0.94   0.345    -.0094589     .027051
              16  |    .009562   .0089541     1.07   0.286    -.0079876    .0271116
              17  |   .0102968   .0086043     1.20   0.231    -.0065674    .0271609
              18  |   .0110004   .0082649     1.33   0.183    -.0051985    .0271992
              19  |   .0116727   .0079359     1.47   0.141    -.0038813    .0272267
              20  |   .0123139   .0076175     1.62   0.106     -.002616    .0272438
              21  |   .0129239   .0073098     1.77   0.077    -.0014032    .0272509
              22  |   .0135026   .0070132     1.93   0.054     -.000243    .0272482
              23  |   .0140502   .0067277     2.09   0.037     .0008641    .0272363
              24  |   .0145665   .0064536     2.26   0.024     .0019177    .0272154
              25  |   .0150517   .0061911     2.43   0.015     .0029173     .027186
              26  |   .0155056   .0059404     2.61   0.009     .0038626    .0271485
              27  |   .0159283   .0057017     2.79   0.005     .0047532    .0271035
              28  |   .0163199   .0054753     2.98   0.003     .0055885    .0270512
              29  |   .0166802   .0052613     3.17   0.002     .0063683    .0269921
              30  |   .0170093   .0050599     3.36   0.001      .007092    .0269266
              31  |   .0173072   .0048714     3.55   0.000     .0077595     .026855
              32  |   .0175739   .0046958     3.74   0.000     .0083703    .0267776
              33  |   .0178095   .0045333     3.93   0.000     .0089244    .0266945
              34  |   .0180138   .0043838     4.11   0.000     .0094217    .0266059
              35  |   .0181869   .0042474     4.28   0.000     .0098621    .0265116
              36  |   .0183288   .0041239     4.44   0.000     .0102461    .0264115
              37  |   .0184395   .0040131     4.59   0.000     .0105738    .0263051
              38  |   .0185189   .0039148     4.73   0.000      .010846    .0261919
              39  |   .0185672   .0038286     4.85   0.000     .0110634    .0260711
              40  |   .0185843   .0037538     4.95   0.000     .0112269    .0259417
              41  |   .0185702   .0036901     5.03   0.000     .0113378    .0258026
              42  |   .0185249   .0036366     5.09   0.000     .0113973    .0256524
              43  |   .0184483   .0035926     5.14   0.000      .011407    .0254896
              44  |   .0183406   .0035572     5.16   0.000     .0113685    .0253127
              45  |   .0182017   .0035298     5.16   0.000     .0112834    .0251199
              46  |   .0180315   .0035092     5.14   0.000     .0111536    .0249095
              47  |   .0178302   .0034947     5.10   0.000     .0109806    .0246797
              48  |   .0175976   .0034854     5.05   0.000     .0107664    .0244288
              49  |   .0173338   .0034803     4.98   0.000     .0105125    .0241552
              50  |   .0170389   .0034787     4.90   0.000     .0102207    .0238571
              51  |   .0167127   .0034798     4.80   0.000     .0098924     .023533
              52  |   .0163554   .0034828     4.70   0.000     .0095291    .0231816
              53  |   .0159668   .0034871     4.58   0.000     .0091322    .0228014
              54  |    .015547   .0034921     4.45   0.000     .0087027    .0223913
              55  |    .015096   .0034971     4.32   0.000     .0082419    .0219502
              56  |   .0146138   .0035017     4.17   0.000     .0077506     .021477
              57  |   .0141004   .0035055     4.02   0.000     .0072298    .0209711
              58  |   .0135558   .0035081     3.86   0.000     .0066801    .0204315
              59  |     .01298   .0035091     3.70   0.000     .0061023    .0198578
              60  |    .012373   .0035084     3.53   0.000     .0054967    .0192493
              61  |   .0117348   .0035056     3.35   0.001     .0048639    .0186058
              62  |   .0110654   .0035008     3.16   0.002      .004204    .0179268
              63  |   .0103648   .0034936     2.97   0.003     .0035174    .0172122
              64  |    .009633   .0034842     2.76   0.006      .002804     .016462
              65  |     .00887   .0034725     2.55   0.011     .0020639     .015676
              66  |   .0080757   .0034586     2.33   0.020     .0012969    .0148546
              67  |   .0072503   .0034426     2.11   0.035     .0005028    .0139978
              68  |   .0063937   .0034247     1.87   0.062    -.0003187     .013106
              69  |   .0055058   .0034051     1.62   0.106    -.0011681    .0121798
              70  |   .0045868   .0033842     1.36   0.175    -.0020461    .0112196
              71  |   .0036365   .0033622     1.08   0.279    -.0029532    .0102263
              72  |   .0026551   .0033396     0.80   0.427    -.0038904    .0092006
              73  |   .0016424    .003317     0.50   0.620    -.0048587    .0081435
              74  |   .0005986   .0032948     0.18   0.856    -.0058592    .0070563
              75  |  -.0004765   .0032739    -0.15   0.884    -.0068932    .0059402
              76  |  -.0015828   .0032548    -0.49   0.627    -.0079621    .0047966
              77  |  -.0027202   .0032385    -0.84   0.401    -.0090676    .0036271
              78  |  -.0038889   .0032258    -1.21   0.228    -.0102114    .0024335
              79  |  -.0050888   .0032177    -1.58   0.114    -.0113953    .0012177
              80  |  -.0063199   .0032151    -1.97   0.049    -.0126215   -.0000183
              81  |  -.0075822   .0032193    -2.36   0.019    -.0138918   -.0012726
              82  |  -.0088757   .0032311    -2.75   0.006    -.0152085   -.0025429
              83  |  -.0102004   .0032517    -3.14   0.002    -.0165736   -.0038272
              84  |  -.0115563   .0032822    -3.52   0.000    -.0179892   -.0051234
              85  |  -.0129434   .0033234    -3.89   0.000    -.0194572   -.0064296
              86  |  -.0143617   .0033764    -4.25   0.000    -.0209793   -.0077441
              87  |  -.0158112   .0034418    -4.59   0.000    -.0225571   -.0090654
              88  |  -.0172919   .0035205    -4.91   0.000    -.0241919    -.010392
              89  |  -.0188039   .0036127    -5.20   0.000    -.0258847    -.011723
              90  |   -.020347   .0037191    -5.47   0.000    -.0276362   -.0130578
              91  |  -.0219213   .0038397    -5.71   0.000     -.029447   -.0143957
              92  |  -.0235269   .0039747    -5.92   0.000    -.0313171   -.0157366
              93  |  -.0251636   .0041241    -6.10   0.000    -.0332466   -.0170806
              94  |  -.0268316   .0042877    -6.26   0.000    -.0352353   -.0184278
              95  |  -.0285307   .0044654    -6.39   0.000    -.0372828   -.0197786
              96  |  -.0302611    .004657    -6.50   0.000    -.0393887   -.0211335
              97  |  -.0320226   .0048622    -6.59   0.000    -.0415523   -.0224929
              98  |  -.0338154   .0050806    -6.66   0.000    -.0437732   -.0238576
              99  |  -.0356394    .005312    -6.71   0.000    -.0460506   -.0252281
             100  |  -.0374945    .005556    -6.75   0.000     -.048384    -.026605
             101  |  -.0393809   .0058123    -6.78   0.000    -.0507727    -.027989
-----------------------------------------------------------------------------------

. marginsplot, recast(line) recastci(rarea) xtitle("Lagged Nuclear Latency") ytitle("Effects on Nuclear Latency") title("Marginal Effects o
> f US Signals of Support on Nuclear Latency") level(95)

Variables that uniquely identify margins: Nu_std_lagged

. * Figure 4
. 
. 
. 
. ********************************************************************************************************
. *Table 4
. 
. use "nuclear_latency_panel.dta", clear
(Written by R.              )

. 
. sort ccode year

. xi i.year
i.year            _Iyear_1950-2010    (naturally coded; _Iyear_1950 omitted)

. 
. xtset ccode year

Panel variable: ccode (unbalanced)
 Time variable: year, 1950 to 2010, but with a gap
         Delta: 1 unit

. 
. 
. gen a = l.Nu_std
(200 missing values generated)

. gen b = l2.Nu_std
(399 missing values generated)

. gen Nu_std_lagged = l3.Nu_std
(595 missing values generated)

. 
. gen support_US_lagged = l3.support_US_std
(594 missing values generated)

. gen support_USSR_lagged = l3.support_USSR_std
(594 missing values generated)

. gen support_UK_lagged = l3.support_UK_std
(594 missing values generated)

. gen support_France_lagged = l3.support_France_std
(594 missing values generated)

. gen support_China_lagged = l3.support_China_std
(594 missing values generated)

. 
. 
. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,092
Group variable: ccode                           Number of groups  =        195

R-squared:                                      Obs per group:
     Within  = 0.8951                                         min =          2
     Between = 0.9965                                         avg =       41.5
     Overall = 0.9754                                         max =         58

                                                F(5,194)          =    3826.78
corr(u_i, Xb) = 0.8222                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 195 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .7452075   .0265008    28.12   0.000     .6929408    .7974742
                                  support_US_lagged |  -.0373146   .0281475    -1.33   0.187     -.092829    .0181998
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .3313801   .0983872     3.37   0.001     .1373343    .5254259
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |    .152911   .0240689     6.35   0.000     .1054407    .2003812
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |  -.3701578   .0814838    -4.54   0.000    -.5308657     -.20945
                                                    |
                                              _cons |   .0922131   .0064338    14.33   0.000      .079524    .1049022
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .03739028
                                            sigma_e |  .03523556
                                                rho |  .52964268   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. estimates store m1

. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged l4.support_USSR_std l4.support_Ch
> ina_std l4.support_UK_std l4.support_France_std l4.cinc l4.country_dem l4.ln_GNP l4.i.mid l4.IdealPointDistance_US, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      7,004
Group variable: ccode                           Number of groups  =        191

R-squared:                                      Obs per group:
     Within  = 0.8898                                         min =          1
     Between = 0.9939                                         avg =       36.7
     Overall = 0.9748                                         max =         56

                                                F(14,190)         =    1394.38
corr(u_i, Xb) = 0.8047                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 191 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .6371488   .0292885    21.75   0.000     .5793764    .6949212
                                  support_US_lagged |  -.0744988   .0317398    -2.35   0.020    -.1371065   -.0118911
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .4906579   .1132678     4.33   0.000     .2672339    .7140818
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .1840087   .0278902     6.60   0.000     .1289946    .2390228
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |  -.5339605   .0923756    -5.78   0.000     -.716174    -.351747
                                                    |
                                   support_USSR_std |
                                                L4. |   .0019143   .0085234     0.22   0.823    -.0148983     .018727
                                                    |
                                  support_China_std |
                                                L4. |   .0125694   .0052118     2.41   0.017      .002289    .0228497
                                                    |
                                     support_UK_std |
                                                L4. |  -.0209538   .0062397    -3.36   0.001    -.0332618   -.0086459
                                                    |
                                 support_France_std |
                                                L4. |   .0096806   .0033964     2.85   0.005      .002981    .0163801
                                                    |
                                               cinc |
                                                L4. |   1.576171   .6245309     2.52   0.012      .344266    2.808076
                                                    |
                                        country_dem |
                                                L4. |  -.0014512   .0018436    -0.79   0.432    -.0050878    .0021854
                                                    |
                                             ln_GNP |
                                                L4. |   .0064835   .0015796     4.10   0.000     .0033678    .0095992
                                                    |
                                             L4.mid |
                                                 1  |  -.0004886   .0015799    -0.31   0.757    -.0036051    .0026279
                                                    |
                              IdealPointDistance_US |
                                                L4. |   .0017003   .0015113     1.13   0.262    -.0012808    .0046814
                                                    |
                                              _cons |  -.0183655   .0304725    -0.60   0.547    -.0784734    .0417425
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .04356658
                                            sigma_e |   .0330891
                                                rho |  .63417568   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. estimates store m2

. 
. esttab m1 m2 using Table4.tex, se star(+ 0.10 * 0.05 ** 0.01) replace
(output written to Table4.tex)

. 
. 
. xtreg Nu_std c.Nu_std_lagged##c.support_US_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_US_lagged l4.support_USSR_std l4.support_Ch
> ina_std l4.support_UK_std l4.support_France_std l4.cinc l4.country_dem l4.ln_GNP l4.i.mid l4.IdealPointDistance_US, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_US_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      7,004
Group variable: ccode                           Number of groups  =        191

R-squared:                                      Obs per group:
     Within  = 0.8898                                         min =          1
     Between = 0.9939                                         avg =       36.7
     Overall = 0.9748                                         max =         56

                                                F(14,190)         =    1394.38
corr(u_i, Xb) = 0.8047                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 191 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .6371488   .0292885    21.75   0.000     .5793764    .6949212
                                  support_US_lagged |  -.0744988   .0317398    -2.35   0.020    -.1371065   -.0118911
                                                    |
                c.Nu_std_lagged#c.support_US_lagged |   .4906579   .1132678     4.33   0.000     .2672339    .7140818
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .1840087   .0278902     6.60   0.000     .1289946    .2390228
                                                    |
                                  support_US_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_US_lagged |  -.5339605   .0923756    -5.78   0.000     -.716174    -.351747
                                                    |
                                   support_USSR_std |
                                                L4. |   .0019143   .0085234     0.22   0.823    -.0148983     .018727
                                                    |
                                  support_China_std |
                                                L4. |   .0125694   .0052118     2.41   0.017      .002289    .0228497
                                                    |
                                     support_UK_std |
                                                L4. |  -.0209538   .0062397    -3.36   0.001    -.0332618   -.0086459
                                                    |
                                 support_France_std |
                                                L4. |   .0096806   .0033964     2.85   0.005      .002981    .0163801
                                                    |
                                               cinc |
                                                L4. |   1.576171   .6245309     2.52   0.012      .344266    2.808076
                                                    |
                                        country_dem |
                                                L4. |  -.0014512   .0018436    -0.79   0.432    -.0050878    .0021854
                                                    |
                                             ln_GNP |
                                                L4. |   .0064835   .0015796     4.10   0.000     .0033678    .0095992
                                                    |
                                             L4.mid |
                                                 1  |  -.0004886   .0015799    -0.31   0.757    -.0036051    .0026279
                                                    |
                              IdealPointDistance_US |
                                                L4. |   .0017003   .0015113     1.13   0.262    -.0012808    .0046814
                                                    |
                                              _cons |  -.0183655   .0304725    -0.60   0.547    -.0784734    .0417425
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .04356658
                                            sigma_e |   .0330891
                                                rho |  .63417568   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. margins, dydx(support_US_lagged) at(Nu_std_lagged = (0(0.01)1)) force

Average marginal effects                                 Number of obs = 7,004
Model VCE: Robust

Expression: Linear prediction, predict()
dy/dx wrt:  support_US_lagged
1._at:   Nu_std_lagged =   0
2._at:   Nu_std_lagged = .01
3._at:   Nu_std_lagged = .02
4._at:   Nu_std_lagged = .03
5._at:   Nu_std_lagged = .04
6._at:   Nu_std_lagged = .05
7._at:   Nu_std_lagged = .06
8._at:   Nu_std_lagged = .07
9._at:   Nu_std_lagged = .08
10._at:  Nu_std_lagged = .09
11._at:  Nu_std_lagged =  .1
12._at:  Nu_std_lagged = .11
13._at:  Nu_std_lagged = .12
14._at:  Nu_std_lagged = .13
15._at:  Nu_std_lagged = .14
16._at:  Nu_std_lagged = .15
17._at:  Nu_std_lagged = .16
18._at:  Nu_std_lagged = .17
19._at:  Nu_std_lagged = .18
20._at:  Nu_std_lagged = .19
21._at:  Nu_std_lagged =  .2
22._at:  Nu_std_lagged = .21
23._at:  Nu_std_lagged = .22
24._at:  Nu_std_lagged = .23
25._at:  Nu_std_lagged = .24
26._at:  Nu_std_lagged = .25
27._at:  Nu_std_lagged = .26
28._at:  Nu_std_lagged = .27
29._at:  Nu_std_lagged = .28
30._at:  Nu_std_lagged = .29
31._at:  Nu_std_lagged =  .3
32._at:  Nu_std_lagged = .31
33._at:  Nu_std_lagged = .32
34._at:  Nu_std_lagged = .33
35._at:  Nu_std_lagged = .34
36._at:  Nu_std_lagged = .35
37._at:  Nu_std_lagged = .36
38._at:  Nu_std_lagged = .37
39._at:  Nu_std_lagged = .38
40._at:  Nu_std_lagged = .39
41._at:  Nu_std_lagged =  .4
42._at:  Nu_std_lagged = .41
43._at:  Nu_std_lagged = .42
44._at:  Nu_std_lagged = .43
45._at:  Nu_std_lagged = .44
46._at:  Nu_std_lagged = .45
47._at:  Nu_std_lagged = .46
48._at:  Nu_std_lagged = .47
49._at:  Nu_std_lagged = .48
50._at:  Nu_std_lagged = .49
51._at:  Nu_std_lagged =  .5
52._at:  Nu_std_lagged = .51
53._at:  Nu_std_lagged = .52
54._at:  Nu_std_lagged = .53
55._at:  Nu_std_lagged = .54
56._at:  Nu_std_lagged = .55
57._at:  Nu_std_lagged = .56
58._at:  Nu_std_lagged = .57
59._at:  Nu_std_lagged = .58
60._at:  Nu_std_lagged = .59
61._at:  Nu_std_lagged =  .6
62._at:  Nu_std_lagged = .61
63._at:  Nu_std_lagged = .62
64._at:  Nu_std_lagged = .63
65._at:  Nu_std_lagged = .64
66._at:  Nu_std_lagged = .65
67._at:  Nu_std_lagged = .66
68._at:  Nu_std_lagged = .67
69._at:  Nu_std_lagged = .68
70._at:  Nu_std_lagged = .69
71._at:  Nu_std_lagged =  .7
72._at:  Nu_std_lagged = .71
73._at:  Nu_std_lagged = .72
74._at:  Nu_std_lagged = .73
75._at:  Nu_std_lagged = .74
76._at:  Nu_std_lagged = .75
77._at:  Nu_std_lagged = .76
78._at:  Nu_std_lagged = .77
79._at:  Nu_std_lagged = .78
80._at:  Nu_std_lagged = .79
81._at:  Nu_std_lagged =  .8
82._at:  Nu_std_lagged = .81
83._at:  Nu_std_lagged = .82
84._at:  Nu_std_lagged = .83
85._at:  Nu_std_lagged = .84
86._at:  Nu_std_lagged = .85
87._at:  Nu_std_lagged = .86
88._at:  Nu_std_lagged = .87
89._at:  Nu_std_lagged = .88
90._at:  Nu_std_lagged = .89
91._at:  Nu_std_lagged =  .9
92._at:  Nu_std_lagged = .91
93._at:  Nu_std_lagged = .92
94._at:  Nu_std_lagged = .93
95._at:  Nu_std_lagged = .94
96._at:  Nu_std_lagged = .95
97._at:  Nu_std_lagged = .96
98._at:  Nu_std_lagged = .97
99._at:  Nu_std_lagged = .98
100._at: Nu_std_lagged = .99
101._at: Nu_std_lagged =   1

-----------------------------------------------------------------------------------
                  |            Delta-method
                  |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
------------------+----------------------------------------------------------------
support_US_lagged |
              _at |
               1  |  -.0744988   .0317398    -2.35   0.019    -.1367077   -.0122899
               2  |  -.0696456     .03069    -2.27   0.023    -.1297969   -.0094943
               3  |  -.0648992   .0296609    -2.19   0.029    -.1230334   -.0067649
               4  |  -.0602596   .0286526    -2.10   0.035    -.1164177   -.0041015
               5  |  -.0557268   .0276654    -2.01   0.044      -.10995   -.0015036
               6  |  -.0513008   .0266994    -1.92   0.055    -.1036306    .0010291
               7  |  -.0469816   .0257548    -1.82   0.068    -.0974601     .003497
               8  |  -.0427691   .0248319    -1.72   0.085    -.0914387    .0059004
               9  |  -.0386635   .0239308    -1.62   0.106    -.0855669    .0082399
              10  |  -.0346646   .0230518    -1.50   0.133    -.0798453     .010516
              11  |  -.0307726   .0221952    -1.39   0.166    -.0742743    .0127292
              12  |  -.0269873   .0213612    -1.26   0.206    -.0688546    .0148799
              13  |  -.0233089   .0205503    -1.13   0.257    -.0635867     .016969
              14  |  -.0197372   .0197627    -1.00   0.318    -.0584713     .018997
              15  |  -.0162723   .0189988    -0.86   0.392    -.0535092    .0209646
              16  |  -.0129142   .0182589    -0.71   0.479    -.0487011    .0228727
              17  |  -.0096629   .0175436    -0.55   0.582    -.0440477    .0247219
              18  |  -.0065184   .0168532    -0.39   0.699    -.0395501    .0265133
              19  |  -.0034807   .0161882    -0.22   0.830     -.035209    .0282477
              20  |  -.0005497   .0155491    -0.04   0.972    -.0310255     .029926
              21  |   .0022744   .0149365     0.15   0.879    -.0270005    .0315493
              22  |   .0049917   .0143507     0.35   0.728    -.0231352    .0331186
              23  |   .0076023   .0137924     0.55   0.582    -.0194304    .0346349
              24  |    .010106   .0132621     0.76   0.446    -.0158873    .0360993
              25  |    .012503   .0127603     0.98   0.327    -.0125068    .0375128
              26  |   .0147932   .0122875     1.20   0.229    -.0092899    .0388763
              27  |   .0169765   .0118441     1.43   0.152    -.0062375    .0401906
              28  |   .0190531   .0114305     1.67   0.096    -.0033503    .0414566
              29  |   .0210229   .0110471     1.90   0.057    -.0006289    .0426748
              30  |   .0228859   .0106938     2.14   0.032     .0019265    .0438454
              31  |   .0246422   .0103708     2.38   0.017     .0043157    .0449686
              32  |   .0262916    .010078     2.61   0.009     .0065391     .046044
              33  |   .0278342   .0098149     2.84   0.005     .0085973     .047071
              34  |     .02927   .0095811     3.05   0.002     .0104915    .0480486
              35  |   .0305991   .0093757     3.26   0.001      .012223    .0489752
              36  |   .0318213   .0091979     3.46   0.001     .0137938    .0498488
              37  |   .0329368   .0090463     3.64   0.000     .0152064    .0506671
              38  |   .0339455   .0089195     3.81   0.000     .0164636    .0514274
              39  |   .0348473    .008816     3.95   0.000     .0175683    .0521263
              40  |   .0356424   .0087339     4.08   0.000     .0185243    .0527605
              41  |   .0363307   .0086714     4.19   0.000      .019335    .0533264
              42  |   .0369122   .0086266     4.28   0.000     .0200044      .05382
              43  |   .0373869   .0085974     4.35   0.000     .0205363    .0542375
              44  |   .0377548   .0085818     4.40   0.000     .0209347    .0545749
              45  |   .0380159    .008578     4.43   0.000     .0212034    .0548284
              46  |   .0381703   .0085839     4.45   0.000     .0213462    .0549943
              47  |   .0382178   .0085977     4.45   0.000     .0213666    .0550691
              48  |   .0381586   .0086179     4.43   0.000     .0212679    .0550492
              49  |   .0379925   .0086426     4.40   0.000     .0210533    .0549318
              50  |   .0377197   .0086706     4.35   0.000     .0207256    .0547138
              51  |     .03734   .0087005     4.29   0.000     .0202875    .0543926
              52  |   .0368536    .008731     4.22   0.000     .0197413     .053966
              53  |   .0362604   .0087611     4.14   0.000     .0190891    .0534318
              54  |   .0355604   .0087898     4.05   0.000     .0183327    .0527881
              55  |   .0347536   .0088164     3.94   0.000     .0174737    .0520335
              56  |     .03384   .0088402     3.83   0.000     .0165135    .0511665
              57  |   .0328196   .0088606     3.70   0.000     .0154532    .0501861
              58  |   .0316925   .0088771     3.57   0.000     .0142936    .0490913
              59  |   .0304585   .0088895     3.43   0.001     .0130354    .0478816
              60  |   .0291177   .0088975     3.27   0.001      .011679    .0465564
              61  |   .0276702   .0089009     3.11   0.002     .0102247    .0451157
              62  |   .0261158   .0088999     2.93   0.003     .0086724    .0435593
              63  |   .0244547   .0088944     2.75   0.006     .0070219    .0418875
              64  |   .0226868   .0088848     2.55   0.011     .0052729    .0401007
              65  |   .0208121   .0088713     2.35   0.019     .0034246    .0381995
              66  |   .0188305   .0088544     2.13   0.033     .0014763    .0361848
              67  |   .0167422   .0088346     1.90   0.058    -.0005732    .0340577
              68  |   .0145471   .0088126     1.65   0.099    -.0027252    .0318194
              69  |   .0122453   .0087891     1.39   0.164    -.0049811    .0294716
              70  |   .0098366   .0087652     1.12   0.262    -.0073429    .0270161
              71  |   .0073211   .0087418     0.84   0.402    -.0098126    .0244548
              72  |   .0046988   .0087202     0.54   0.590    -.0123923      .02179
              73  |   .0019698   .0087015     0.23   0.821    -.0150848    .0190244
              74  |  -.0008661   .0086873    -0.10   0.921    -.0178928    .0161607
              75  |  -.0038087    .008679    -0.44   0.661    -.0208193    .0132019
              76  |  -.0068581   .0086784    -0.79   0.429    -.0238676    .0101513
              77  |  -.0100144   .0086872    -1.15   0.249     -.027041    .0070123
              78  |  -.0132774   .0087073    -1.52   0.127    -.0303434    .0037886
              79  |  -.0166472   .0087405    -1.90   0.057    -.0337783    .0004839
              80  |  -.0201238   .0087888    -2.29   0.022    -.0373496    -.002898
              81  |  -.0237072   .0088542    -2.68   0.007    -.0410611   -.0063533
              82  |  -.0273974   .0089385    -3.07   0.002    -.0449165   -.0098782
              83  |  -.0311943   .0090436    -3.45   0.001    -.0489195   -.0134692
              84  |  -.0350981   .0091712    -3.83   0.000    -.0530734   -.0171229
              85  |  -.0391087    .009323    -4.19   0.000    -.0573813    -.020836
              86  |   -.043226   .0095002    -4.55   0.000    -.0618462   -.0246059
              87  |  -.0474502   .0097043    -4.89   0.000    -.0664702   -.0284301
              88  |  -.0517811   .0099361    -5.21   0.000    -.0712556   -.0323067
              89  |  -.0562188   .0101966    -5.51   0.000    -.0762038   -.0362339
              90  |  -.0607634   .0104862    -5.79   0.000     -.081316   -.0402108
              91  |  -.0654147   .0108055    -6.05   0.000     -.086593   -.0442364
              92  |  -.0701728   .0111545    -6.29   0.000    -.0920352   -.0483104
              93  |  -.0750377   .0115334    -6.51   0.000    -.0976427   -.0524327
              94  |  -.0800094    .011942    -6.70   0.000    -.1034153   -.0566035
              95  |  -.0850879   .0123801    -6.87   0.000    -.1093525   -.0608233
              96  |  -.0902731   .0128475    -7.03   0.000    -.1154537   -.0650926
              97  |  -.0955652   .0133436    -7.16   0.000    -.1217182   -.0694122
              98  |  -.1009641   .0138681    -7.28   0.000    -.1281451    -.073783
              99  |  -.1064697   .0144206    -7.38   0.000    -.1347335    -.078206
             100  |  -.1120822   .0150004    -7.47   0.000    -.1414824   -.0826819
             101  |  -.1178014   .0156071    -7.55   0.000    -.1483908    -.087212
-----------------------------------------------------------------------------------

. marginsplot, recast(line) recastci(rarea) xtitle("Lagged Nuclear Latency") ytitle("Effects on Nuclear Latency") title("Marginal Effects o
> f US Signals of Support on Nuclear Latency") level(95)

Variables that uniquely identify margins: Nu_std_lagged

. * Figure 5
. 
. 
. ********************************************************************************************************
. *Table 5
. 
. use "nuclear_latency_panel.dta", clear
(Written by R.              )

. 
. sort ccode year

. xi i.year
i.year            _Iyear_1950-2010    (naturally coded; _Iyear_1950 omitted)

. 
. xtset ccode year

Panel variable: ccode (unbalanced)
 Time variable: year, 1950 to 2010, but with a gap
         Delta: 1 unit

. 
. gen Nu_std_lagged = l.Nu_std
(200 missing values generated)

. 
. gen support_US_lagged = l.support_US_std
(199 missing values generated)

. gen support_USSR_lagged = l.support_USSR_std
(199 missing values generated)

. gen support_UK_lagged = l.support_UK_std
(199 missing values generated)

. gen support_France_lagged = l.support_France_std
(199 missing values generated)

. gen support_China_lagged = l.support_China_std
(199 missing values generated)

. 
. 
. xtreg Nu_std c.Nu_std_lagged##c.support_USSR_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_USSR_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_USSR_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,487
Group variable: ccode                           Number of groups  =        198

R-squared:                                      Obs per group:
     Within  = 0.9647                                         min =          1
     Between = 0.9996                                         avg =       42.9
     Overall = 0.9923                                         max =         60

                                                F(5,197)          =   36621.59
corr(u_i, Xb) = 0.8168                          Prob > F          =     0.0000

                                                                         (Std. err. adjusted for 198 clusters in ccode)
-----------------------------------------------------------------------------------------------------------------------
                                                      |               Robust
                                               Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------------------------------------------+----------------------------------------------------------------
                                        Nu_std_lagged |    .918917     .00939    97.86   0.000     .9003991    .9374349
                                  support_USSR_lagged |  -.0455003   .0183162    -2.48   0.014    -.0816212   -.0093793
                                                      |
                c.Nu_std_lagged#c.support_USSR_lagged |   .2062535   .0646097     3.19   0.002     .0788381    .3336689
                                                      |
                                        Nu_std_lagged |          0  (omitted)
                                                      |
                      c.Nu_std_lagged#c.Nu_std_lagged |   .0410369   .0080289     5.11   0.000     .0252032    .0568705
                                                      |
                                  support_USSR_lagged |          0  (omitted)
                                                      |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_USSR_lagged |  -.1767814   .0521856    -3.39   0.001    -.2796956   -.0738672
                                                      |
                                                _cons |   .0316842   .0023641    13.40   0.000     .0270219    .0363464
------------------------------------------------------+----------------------------------------------------------------
                                              sigma_u |  .01220079
                                              sigma_e |  .02158639
                                                  rho |  .24211374   (fraction of variance due to u_i)
-----------------------------------------------------------------------------------------------------------------------

. estimates store k1

. 
. xtreg Nu_std c.Nu_std_lagged##c.support_China_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_China_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_China_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,487
Group variable: ccode                           Number of groups  =        198

R-squared:                                      Obs per group:
     Within  = 0.9649                                         min =          1
     Between = 0.9995                                         avg =       42.9
     Overall = 0.9921                                         max =         60

                                                F(5,197)          =   29120.11
corr(u_i, Xb) = 0.8314                          Prob > F          =     0.0000

                                                                          (Std. err. adjusted for 198 clusters in ccode)
------------------------------------------------------------------------------------------------------------------------
                                                       |               Robust
                                                Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------------------------------------+----------------------------------------------------------------
                                         Nu_std_lagged |   .9181932   .0107613    85.32   0.000      .896971    .9394153
                                  support_China_lagged |   .0347872   .0184157     1.89   0.060      -.00153    .0711045
                                                       |
                c.Nu_std_lagged#c.support_China_lagged |  -.0078256   .0648751    -0.12   0.904    -.1357644    .1201132
                                                       |
                                         Nu_std_lagged |          0  (omitted)
                                                       |
                       c.Nu_std_lagged#c.Nu_std_lagged |   .0481806   .0092025     5.24   0.000     .0300327    .0663286
                                                       |
                                  support_China_lagged |          0  (omitted)
                                                       |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_China_lagged |  -.0510922   .0532593    -0.96   0.339    -.1561236    .0539393
                                                       |
                                                 _cons |   .0276107   .0027857     9.91   0.000      .022117    .0331044
-------------------------------------------------------+----------------------------------------------------------------
                                               sigma_u |  .01482344
                                               sigma_e |  .02154368
                                                   rho |  .32131264   (fraction of variance due to u_i)
------------------------------------------------------------------------------------------------------------------------

. estimates store k2

. 
. xtreg Nu_std c.Nu_std_lagged##c.support_UK_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_UK_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_UK_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,487
Group variable: ccode                           Number of groups  =        198

R-squared:                                      Obs per group:
     Within  = 0.9647                                         min =          1
     Between = 0.9996                                         avg =       42.9
     Overall = 0.9923                                         max =         60

                                                F(5,197)          =   46875.41
corr(u_i, Xb) = 0.8280                          Prob > F          =     0.0000

                                                                       (Std. err. adjusted for 198 clusters in ccode)
---------------------------------------------------------------------------------------------------------------------
                                                    |               Robust
                                             Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------------------------------------+----------------------------------------------------------------
                                      Nu_std_lagged |   .9165426    .009353    97.99   0.000     .8980977    .9349874
                                  support_UK_lagged |  -.0215699   .0105198    -2.05   0.042    -.0423158   -.0008239
                                                    |
                c.Nu_std_lagged#c.support_UK_lagged |   .1190852   .0347036     3.43   0.001     .0506469    .1875234
                                                    |
                                      Nu_std_lagged |          0  (omitted)
                                                    |
                    c.Nu_std_lagged#c.Nu_std_lagged |   .0475217   .0081238     5.85   0.000     .0315009    .0635424
                                                    |
                                  support_UK_lagged |          0  (omitted)
                                                    |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_UK_lagged |  -.1227742   .0290229    -4.23   0.000    -.1800098   -.0655387
                                                    |
                                              _cons |   .0318048   .0022866    13.91   0.000     .0272954    .0363142
----------------------------------------------------+----------------------------------------------------------------
                                            sigma_u |  .01263368
                                            sigma_e |  .02159097
                                                rho |  .25505754   (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------------------------------

. estimates store k3

. 
. xtreg Nu_std c.Nu_std_lagged##c.support_France_lagged c.Nu_std_lagged##c.Nu_std_lagged##c.support_France_lagged, fe cluster(ccode)
note: Nu_std_lagged omitted because of collinearity.
note: support_France_lagged omitted because of collinearity.

Fixed-effects (within) regression               Number of obs     =      8,487
Group variable: ccode                           Number of groups  =        198

R-squared:                                      Obs per group:
     Within  = 0.9648                                         min =          1
     Between = 0.9996                                         avg =       42.9
     Overall = 0.9923                                         max =         60

                                                F(5,197)          =   45041.05
corr(u_i, Xb) = 0.8306                          Prob > F          =     0.0000

                                                                           (Std. err. adjusted for 198 clusters in ccode)
-------------------------------------------------------------------------------------------------------------------------
                                                        |               Robust
                                                 Nu_std | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------------------+----------------------------------------------------------------
                                          Nu_std_lagged |   .9216691   .0105837    87.08   0.000     .9007972    .9425411
                                  support_France_lagged |   .0125844    .012724     0.99   0.324    -.0125083    .0376772
                                                        |
                c.Nu_std_lagged#c.support_France_lagged |   .0229222   .0447206     0.51   0.609    -.0652703    .1111147
                                                        |
                                          Nu_std_lagged |          0  (omitted)
                                                        |
                        c.Nu_std_lagged#c.Nu_std_lagged |   .0440334   .0091603     4.81   0.000     .0259685    .0620983
                                                        |
                                  support_France_lagged |          0  (omitted)
                                                        |
c.Nu_std_lagged#c.Nu_std_lagged#c.support_France_lagged |  -.0542289   .0364348    -1.49   0.138    -.1260813    .0176234
                                                        |
                                                  _cons |    .029162   .0026401    11.05   0.000     .0239555    .0343686
--------------------------------------------------------+----------------------------------------------------------------
                                                sigma_u |  .01315372
                                                sigma_e |  .02158032
                                                    rho |  .27088166   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------------------------------------

. estimates store k4

. 
. 
. esttab k1 k2 k3 k4 using Table5.tex, se star(+ 0.10 * 0.05 ** 0.01) replace
(output written to Table5.tex)

. 
. 
. log close
      name:  <unnamed>
       log:  C:\My Documents\PSRMLaptop\Hobby\Nuclear Latency\FPA_replication\Analysis_Main_log.log
  log type:  text
 closed on:   1 Nov 2024, 16:29:53
-------------------------------------------------------------------------------------------------------------------------------------------
